mlsanityData to 7 Oct 2026

Attention-based Convolutional Autoencoders for 3D-Variational Data Assimilation

arXiv 2101.02121 ↗First posted 6 Jan 2021cs.LG cs.CEcited by 15

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Abstract (arXiv)

We propose a new 'Bi-Reduced Space' approach to solving 3D Variational Data Assimilation using Convolutional Autoencoders. We prove that our approach has the same solution as previous methods but has significantly lower computational complexity; in other words, we reduce the computational cost without affecting the data assimilation accuracy. We tested the new method with data from a real-world application: a pollution model of a site in Elephant and Castle, London and found that we could reduce the size of the background covariance matrix representation by O(10^3) and, at the same time, increase our data assimilation accuracy with respect to existing reduced space methods.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 36 of its 98 references that are in the map. First posted on arXiv 6 Jan 2021.

Builds on

36 of 98 references.

References · 36

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24 more
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Built on by

Cited by year

Citing papers per year: 2021: 4; 2022: 1; 2023: 4; 2024: 3; 2025: 3.

15 papers.

Sort:

  1. 2023Score-based Data Assimilationcited by 91
  2. 2023Machine learning with data assimilation and uncertainty quantification for dynamical systems: a reviewcited by 74
  3. 2021Latent Space Data Assimilation by using Deep Learningcited by 29
  4. 2021Variational Data Assimilation with a Learned Inverse Observation Operatorcited by 28
  5. 2023FengWu-4DVar: Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilationcited by 22
  6. 2023AI Foundation Models for Weather and Climate: Applications, Design, and Implementationcited by 19
  7. 2021Bridging observation, theory and numerical simulation of the ocean using Machine Learningcited by 15
  8. 2024TorchDA: A Python package for performing data assimilation with deep learning forward and transformation functionscited by 5
  9. 2025Ensemble Kalman filter in latent space using a variational autoencoder paircited by 5
  10. 2021Joint calibration and mapping of satellite altimetry data using trainable variational modelscited by 3
  11. 2022An AI-based Domain-Decomposition Non-Intrusive Reduced-Order Model for Extended Domains applied to Multiphase Flow in Pipescited by 3
  12. 2025Flow-based Bayesian filtering for high-dimensional nonlinear stochastic dynamical systemscited by 3
3 more
  1. 2025Latent Twinscited by 3
  2. 2024VAE-Var: Variational-Autoencoder-Enhanced Variational Assimilationcited by 2
  3. 2024ABCD: Trust enhanced Attention based Convolutional Autoencoder for Risk Assessmentcited by 0